Results 11 to 20 of about 55,134,654 (225)

Light3R-SfM: Towards Feed-forward Structure-from-Motion [PDF]

open access: yes2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
We present Light3R-SfM, a feed-forward, end-to-end learnable framework for efficient large-scale Structure-from-Motion (SfM) from unconstrained image collections. Unlike existing SfM solutions that rely on costly matching and global optimization to achieve accurate 3D reconstructions, Light3R-SfM addresses this limitation through a novel latent global ...
Sven Elflein   +2 more
core   +5 more sources

An assessment of the accuracy of structure-from-motion (SfM) photogrammetry for 3D terrain mapping [PDF]

open access: yesGeomatics, Landmanagement and Landscape, 2020
Unmanned Aerial Vehicles (UAVs) equipped with photogrammetric or remote sensing instrumentations offer numerous opportunities in mapping and data collection for topographic modelling. An example is an emerging technique known as Structure-from-Motion (SfM) photogrammetry used for the collection of low-cost, high spatial resolution, three-dimensional ...
Chima Jude Iheaturu   +2 more
openaire   +4 more sources

Geo-SfM: Teaching geoscientific Structure-from-Motion photogrammetry processing

open access: yes
Latest release of the Geo-SfM eBook that is accessible at https://unisvalbard.github.io/Geo-SfM/.
Betlem, Peter, Rodes, Nil
openaire   +3 more sources

Structure from motion (SFM) photogrammetry [PDF]

open access: yes, 2015
Topographic data measurement is a fundamental aspect of many geomorphic research applications, particularly those including landform monitoring and investigation of changes in topography.
Stuart N. Lane (3777907)   +2 more
core   +6 more sources

On-Barn Pig Weight Estimation Based on Body Measurements by Structure-from-Motion (SfM). [PDF]

open access: yesSensors (Basel), 2018
Information on the body shape of pigs is a key indicator to monitor their performance and health and to control or predict their market weight. Manual measurements are among the most common ways to obtain an indication of animal growth. However, this approach is laborious and difficult, and it may be stressful for both the pigs and the stockman.
Pezzuolo A   +5 more
europepmc   +4 more sources

Dynamics of visual reversals from ambiguous spinning biological-motion and rigid structure-from-motion

open access: yesi-Perception
Three-dimensional rigid structure-from-motion (SFM) and structure from nonrigid biological point-light motion stimuli are perceptually ambiguous. This study investigated the dynamics of perceived reversals in two cases: a spinning point-light walker (PLW)
Leo Poom
doaj   +2 more sources

Multistage SFM: Revisiting Incremental Structure from Motion [PDF]

open access: yes2014 2nd International Conference on 3D Vision, 2014
In this paper, we present a new multistage approach for SfM reconstruction of a single component. Our method begins with building a coarse 3D reconstruction using high-scale features of given images. This step uses only a fraction of features and is fast.
Rajvi Shah   +2 more
openaire   +2 more sources

Rilievo delle lastre tombali del Camposanto Monumentale di Piazza dei Miracoli a Pisa

open access: yesRestauro Archeologico, 2017
The research is aimed at a new photogrammetric survey to tackle the restoration of the gravestones of the Pisa’s monumental cemetery. It is situated in “Piazza del Duomo” and it occupies the north side of the extensive complex.
Giovanni Pancani
doaj   +1 more source

Democratizing photogrammetry: an accuracy perspective

open access: yesGeo-spatial Information Science, 2023
Photogrammetry is experiencing an era of democratization mostly due to the popularity and availability of many commercial off-the-shelf devices, such as drones and smartphones.
Jie Shan   +5 more
doaj   +1 more source

SfM-Net: Learning of Structure and Motion from Video

open access: yesCoRR, 2017
We propose SfM-Net, a geometry-aware neural network for motion estimation in videos that decomposes frame-to-frame pixel motion in terms of scene and object depth, camera motion and 3D object rotations and translations. Given a sequence of frames, SfM-Net predicts depth, segmentation, camera and rigid object motions, converts those into a dense frame ...
Sudheendra Vijayanarasimhan   +4 more
openaire   +3 more sources

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